title: Lower limb wearable capacitive sensing and its applications to recognizing human gaits.
abstract: In this paper, we present an approach to sense human body capacitance and apply it to recognize lower limb locomotion modes. The proposed wearable sensing system includes sensing bands, a signal processing circuit and a gait event detection module. Experiments on long-term working stability, adaptability to disturbance and locomotion mode recognition are carried out to validate the effectiveness of the proposed approach. Twelve able-bodied subjects are recruited, and eleven normal gait modes are investigated. With an event-dependent linear discriminant analysis classifier and feature selection procedure, four time-domain features are used for pattern recognition and satisfactory recognition accuracies (97:3% ± 0:5%, 97:0% ± 0:4%, 95:6% ± 0:9% and 97:0% ± 0:4% for four phases of one gait cycle respectively) are obtained. The accuracies are comparable with that from electromyography-based systems and inertial-based systems. The results validate the effectiveness of the proposed lower limb capacitive sensing approach in recognizing human normal gaits.
authors.affiliation: Intelligent Control Laboratory, College of Engineering, Peking University, Beijing 100871, China. qiningwang@pku.edu.cn.
authors.forename: Enhao
authors.initials: E
authors.lastname: Zheng
authors.forename: Baojun
authors.initials: B
authors.lastname: Chen
authors.forename: Kunlin
authors.initials: K
authors.lastname: Wei
authors.forename: Qining
authors.initials: Q
authors.lastname: Wang
mesh_terms: D056044:Actigraphy / Q000295:instrumentation*; D025802:Electric Capacitance; D004867:Equipment Design; D019544:Equipment Failure Analysis; D005684:Gait / Q000502:physiology*; D006801:Humans; D007866:Leg / Q000502:physiology*; D018670:Monitoring, Ambulatory / Q000295:instrumentation*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014160:Transducers, Pressure